On The Choice of Graph Neural Network Architectures. - Clément Vignac; Guillermo Ortiz-Jiménez; Pascal Frossard (ICASSP, 2020)

Building powerful and equivariant graph neural networks with structural message-passing. - Clément Vignac; Andreas Loukas; Pascal Frossard (NeurIPS, 2020)

Building powerful and equivariant graph neural networks with message-passing. - Clément Vignac; Andreas Loukas; Pascal Frossard (CoRR, 2020)

Modurec: Recommender Systems with Feature and Time Modulation. - Javier Maroto; Clément Vignac; Pascal Frossard (ICASSP, 2021)

Top-N: Equivariant Set and Graph Generation without Exchangeability. - Clément Vignac; Pascal Frossard (ICLR, 2022)

Equivariant Diffusion for Molecule Generation in 3D. - Emiel Hoogeboom; Victor Garcia Satorras; Clément Vignac; Max Welling (ICML, 2022)

Equivariant 3D-Conditional Diffusion Models for Molecular Linker Design. - Ilia Igashov; Hannes Stärk; Clément Vignac; Victor Garcia Satorras; Pascal Frossard; Max Welling; Michael M. Bronstein; Bruno E. Correia (CoRR, 2022)

DiGress: Discrete Denoising diffusion for graph generation. - Clément Vignac; Igor Krawczuk; Antoine Siraudin; Bohan Wang; Volkan Cevher; Pascal Frossard (ICLR, 2023)

MiDi: Mixed Graph and 3D Denoising Diffusion for Molecule Generation. - Clément Vignac; Nagham Osman; Laura Toni; Pascal Frossard (ECML/PKDD (2), 2023)

Sparse Training of Discrete Diffusion Models for Graph Generation. - Yiming Qin; Clément Vignac; Pascal Frossard (CoRR, 2023)

Generative Modelling of Structurally Constrained Graphs. - Manuel Madeira; Clément Vignac; Dorina Thanou; Pascal Frossard (NeurIPS, 2024)

Equivariant 3D-conditional diffusion model for molecular linker design. - Ilia Igashov; Hannes Stärk; Clément Vignac; Arne Schneuing; Victor Garcia Satorras; Pascal Frossard; Max Welling; Michael M. Bronstein; Bruno E. Correia (Nat. Mac. Intell., 2024)

SparseDiff: Sparse Discrete Diffusion for Scalable Graph Generation. - Yiming Qin; Clément Vignac; Pascal Frossard (Trans. Mach. Learn. Res., 2025)